We first measure vibration signals of a variety of failure modes in rotating machinery through a large number of experiments and generate seven mature immune detectors corresponding to seven nondimensional parameters by the artificial immune system.

Step 2

Based on the results obtained from Step 1, we can obtain the index ranges of different faults and calculate the fault features (such as , , and ).

Step 3

We can measure the non-dimensional index to determine the probability of different faults by the mature immune detector. For example, after obtaining a set of experimental data, we use waveform index to determine the fault, and kurtosis index to determine the fault and then we can empirically calculate the basic probability assignment by the cumulative number of experiment results.

Step 4

When we get the diagnosis probability of various indices to different faults by the cumulative proportion of the total number of experiments, we define the diagnosis probability of various indices to different faults as basic probability assignment functions and use evidential theory to aggregate these data.

Step 5

We assume the greatest credibility as a final diagnostic result. That is, the fault is the one with the greatest credibility in the aggregated results.